777 search results for "parallel"

Bivariate linear mixed models using ASReml-R with multiple cores

May 7, 2012
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Bivariate linear mixed models using ASReml-R with multiple cores

A while ago I wanted to run a quantitative genetic analysis where the performance of genotypes in each site was considered as a different trait. If you think about it, with 70 sites and thousands of genotypes one is trying … Continue reading →

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Big Data Analytics with R and Hadoop

May 3, 2012
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The open-source RHadoop project makes it easier to extract data from Hadoop for analysis with R, and to run R within the nodes of the Hadoop cluster -- essentially, to transform Hadoop into a massively-parallel statistical computing cluster based on R. In yesterday's webinar (the replay of which is embedded below), Data scientist and RHadoop project lead Antonio Piccolboni...

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Speeding up R with Intel’s Math Kernel Library (MKL)

May 2, 2012
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Speeding up R with Intel’s Math Kernel Library (MKL)

I did some comparisons of the generic BLAS with Intel's MKL (both sequential and parallel) on a Dell PowerEdge 610 server with dual hyperthreading 6-core 3.06GHz Xeon X5675 processors.  Here are the results from an R benchmarking script (Normal R ...

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Speeding up R with Intel’s Math Kernel Library (MKL)

May 2, 2012
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I did some comparisons of the generic BLAS with Intel's MKL (both sequential and parallel) on a Dell PowerEdge 610 server with dual hyperthreading 6-core 3.06GHz Xeon X5675 processors.  Here are the results from an R benchmarking script (Normal R indicates the generic BLAS,  sMKL is the sequential (single core Intel MKL, and pMKL is the parallel Intel MKL using...

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phyloseq: Reproducible interactive analysis of microbiome census data using R

April 26, 2012
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phyloseq: Reproducible interactive analysis of microbiome census data using R

Collaborative development of phyloseq on GitHub. Official stable release of phyloseq on Bioconductor. Advances in DNA sequencing technology have dramatically improved the scope and scale of culture-independent investigations into microbial communities. There are effective software tools available to process raw DNA … Continue reading →

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AdfTest Function Enhanced With Rcpp Armadillo

April 26, 2012
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In my previous post about rewriting my code to run in parallel part one I mentioned that we will make a small change to adfTest() function as well. In this post we will perform this small but performance-dramatic change. When you take a closer look at the source code of this particular function from fUnitRoots package

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spam evolution

April 26, 2012
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spam evolution

Despite some rather modest protection (like a simple captcha), I still receive spammy comments on this blog every now and again. They’re easily spotted and actually never appear on the website. There’s obviously an incentive for the spammer to post … Continue reading →

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Introduction to Oracle R Connector for Hadoop

April 23, 2012
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MapReduce, the heart of Hadoop, is a programming framework that enables massive scalability across servers using data stored in the Hadoop Distributed File System (HDFS). The Oracle R Connector for Hadoop (ORCH) provides access to a Hadoop cluster from R, enabling manipulation of HDFS-resident data and the execution of MapReduce jobs. Conceptutally, MapReduce is similar...

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Tuning GAMBoost

April 23, 2012
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Tuning GAMBoost

This post describes some of the simulation results which I obtained with the GAMBoost package. The aim of these simulations is to get a feel what I should tune and what I should not tune with GAMBoost. SetupIn the GAMBoost package one can tune qui...

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Visualising the Path of a Genetic Algorithm

April 23, 2012
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Visualising the Path of a Genetic Algorithm

We quite regularly use genetic algorithms to optimise over the ad-hoc functions we develop when trying to solve problems in applied mathematics. However it’s a bit disconcerting to have your algorithm roam through a high dimensional solution space while not being able to picture what it’s doing or how close one solution is to another. … Continue reading...

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